Senior Machine Learning Engineer
Confirmed live in the last 24 hours
Cloud-based AI entreprise solution software
Company Overview
Hive’s mission is to use AI to unlock the next wave of intelligent automation. The company has an industry-leading portfolio of pre-trained models that allow companies of any size to access best-in-class AI solutions at a fraction of the cost and time it would take to build them internally.
AI & Machine Learning
Company Stage
Series D
Total Funding
$155.7M
Founded
2013
Headquarters
San Francisco, California
Growth & Insights
Headcount
6 month growth
↑ 27%1 year growth
↑ 56%2 year growth
↑ 75%Locations
San Francisco, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Computer Vision
Data Analysis
Data Structures & Algorithms
Pytorch
Tensorflow
Natural Language Processing (NLP)
Python
CategoriesNew
AI & Machine Learning
Requirements
- You have a Bachelor's Degree in computer science or a related field
- You have a minimum of 5 years of building production scale ML models
- You know the ins and outs modern machine learning frameworks, such as PyTorch or Tensorflow
- You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
- You have experience writing code and training across distributed systems
- You have an ability to understand and make well-reasoned tradeoffs in designing features
- You can lead end to end development of new products
- You are very knowledgeable in at least one focus area of machine learning, such as computer vision or NLP
- You strongly believe in high code quality, automated testing, and other engineering best practices
- You have attention to detail and a passion for correctness
- You are comfortable with ambiguity and scoping solutions with your teammates
- You have strong interpersonal and communication skills with a bias towards action
Responsibilities
- Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
- Write and maintain scalable, performant and secure code that can be shared across platforms
- Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
- Improve engineering standards, tooling, processes and security
- Develop novel, accurate, and performant ML algorithms for use at scale
- Conduct metric-driven research experiments to improve model performance
- Provide mentorship to and help onboard junior ML engineers
- Collaborate cross-functionally with other teams
- Utilize OWASP top 10 techniques to secure code from vulnerabilities
- Maintain awareness of industry best practices for data maintenance handling as it relates to your role
- Adhere to policies, guidelines and procedures pertaining to the protection of information assets
- Report actual or suspected security and/or policy violations/breaches to an appropriate authority